Show simple item record

dc.contributor.authorFavorov, Alexander
dc.contributor.authorMularoni, Loris
dc.contributor.authorCope, Leslie M.
dc.contributor.authorMedvedeva, Yulia
dc.contributor.authorMironov, Andrey A.
dc.contributor.authorMakeev, Vsevolod J.
dc.contributor.authorWheelan, Sarah J.
dc.date.accessioned2014-08-27T09:44:19Z
dc.date.available2014-08-27T09:44:19Z
dc.date.issued2012-05-31
dc.identifier.citationFavorov A, Mularoni L, Cope LM, Medvedeva Y, Mironov AA, et al. (2012) Exploring Massive, Genome Scale Datasets with the GenometriCorr Package. PLoS Comput Biol 8: e1002529. doi:10.1371/journal.pcbi.1002529.
dc.identifier.issn1553734X
dc.identifier.pmid22693437
dc.identifier.doi10.1371/journal.pcbi.1002529
dc.identifier.urihttp://hdl.handle.net/10754/325275
dc.description.abstractWe have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.
dc.language.isoen
dc.publisherPublic Library of Science (PLoS)
dc.rightsFavorov et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rightsArchived with thanks to PLoS Computational Biology
dc.subjectaccuracy
dc.subjectcomputer interface
dc.subjectcontrolled study
dc.subjectdata analysis software
dc.subjectepigenetics
dc.subjectfungal genome
dc.subjectgene expression profiling
dc.subjectgene insertion
dc.subjectgene sequence
dc.subjectgenetic code
dc.subjectgenetic database
dc.subjecthuman genome
dc.subjectprediction
dc.subjectprocess development
dc.subjectpromoter region
dc.subjectreproducibility
dc.subjectretroposon
dc.subjectRNA gene
dc.subjectsensitivity and specificity
dc.subjecttranscription initiation site
dc.subjectChromosomes
dc.subjectDatabases, Genetic
dc.subjectEpigenomics
dc.subjectGenetic Loci
dc.subjectGenome
dc.subjectGenomics
dc.subjectInformation Storage and Retrieval
dc.subjectInternet
dc.subjectModels, Genetic
dc.subjectModels, Statistical
dc.subjectRNA, Transfer
dc.subjectSoftware
dc.subjectStatistics, Nonparametric
dc.subjectUser-Computer Interface
dc.titleExploring massive, genome scale datasets with the genometricorr package
dc.typeArticle
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.identifier.journalPLoS Computational Biology
dc.identifier.pmcidPMC3364938
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionDepartment of Oncology, Division of Biostatistics and Bioinformatics, Johns Hopkins University School of Medicine, Baltimore, MD, United States
dc.contributor.institutionVavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russian Federation
dc.contributor.institutionResearch Institute of Genetics and Selection of Industrial Microorganisms, Moscow, Russian Federation
dc.contributor.institutionDepartment of Bioengineering and Bioinformatics, Moscow State University, Moscow, Russian Federation
dc.contributor.institutionInstitute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russian Federation
dc.contributor.institutionInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personMedvedeva, Yulia
refterms.dateFOA2018-06-13T14:42:47Z


Files in this item

Thumbnail
Name:
Article-PLoS_Compu-Exploring_-2012.pdf
Size:
2.160Mb
Format:
PDF
Description:
Article - Full Text

This item appears in the following Collection(s)

Show simple item record